August 13, 2018

End-to-end Deep Learning of Optical Fiber Communications

  • Buelow H.
  • Chagnon M.
  • Domanic Lavery
  • Felix Thouin
  • Karanov B.
  • Polina Bayvel
  • Schmalen L.
  • Tobias A. Eriksson

We implement the optical fiber communication system as an end-to-end deep neural network, which includes the complete chain of transmitter, receiver and channel. This approach allows transceiver functions to be optimized in a single end-to-end process. Our work shows that such a deep learning fiber-optic system can achieve reliable communication below forward error correction threshold. In particular we show that for intensity modulation/direct detection systems information rates of 76 Gbps can be achieved at distances beyond 80 km.

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